One can definitely design systems with that performance as an afterthought notion but I'm not sure whether they would be widely used. Would Google or Amazon have been that popular if they had taken minutes to search for content or books? I bet not. Would Porsche, Ferrari or Stealth Bomber have been possible with the performance-as- afterthought process? I bet not. They were built ground up for performance and speed and they live up to those standards. Why should you believe me? I've driven every single one of them. In my dreams. Every night. Seriously.
So, how does one approach thinking about performance at the design phase? Does one need to employ different design principles for different delivery channels? Though there are specialized patterns which cater to a specific delivery channel like Web, Mobile or desktop based solution but there are some which are overarching and can be applied regardless the delivery channel. IMHO, one needs to consider the following -
- Caching - Caching of data can dramatically increase the responsiveness of any application though certain considerations need to be made before finalizing the strategy. One could follow W3 of Caching - What, When and Where.
- What to Cache - It really depends on the application context but anything that would take inordinate amount of time to retrieve and doesn't change that frequently is a good candidate for caching. I also always think about the memory footprint of the cache. I would look at the size of the every object that needs to be cached by enumerating over its properties and computing the actual memory it is going to consume. This helps in the Where part of the puzzle.
- When to Cache - One really has two options around it - Proactive or Reactive. Proactive Caching is generally employed for datasets(Not the ADO.NET DataSet) that get used in the application in most of the scenarios. It is a technique by which one loads the dataset at the start of the application. Reactive Caching is used when one is not sure when a dataset would get used thus it gets cached it after its first retrieval.
- Where to Cache - It depends upon how fast the cached dataset needs to be accessed and how big it is? If the cached data doesn't need to be loaded in fractions of milliseconds and is huge then it makes sense to use an Out of Process Cache. But, if the size of the dataset is not that big then one can think about caching the data in the same process. In-process caching gets a little tricky for the web delivery channel when one has a cluster of web servers. As the cache needs to be identical in all the webservers, one has to either develop something in house or use sophisticated products like NCache to replicate the cache state among the clusters.
- Data Structures - Poor selection of data structures can lead to lot of memory wastage and denegenration of performance. Would you really use a LinkedList for storing all your Customers? Would you use an Array for dataset that is always changing? Probably not. I think one needs to decide early the data structures which would get used in the domain model of the product.
- Algorithms - One not only needs to use the right data structures to store the data but also use the right algorithms to insert/retrieve the data from them. They are tightly coupled and both of them have to be selected in tandem. If you were to sort your dataset, would you use BubbleSort or QuickSort? You wouldn't care if the dataset is too small but using BubbleSort in large datasets could be an extreme wastage of CPU cycles. The selection of the right algorithm plays a huge part in the responsiveness of your application and it makes sense to give a lot of thought to it.
- Asynchronous Behavior - I'm not sure whether asynchronous behavior can increase the response times of your application but they can tremendously increase the responsivess of your application. In the world of short attention spans and even smaller patience levels, responsiveness means performance. One can use variety of techniques to break the long running transactions and execute them in a step manner while engaging the user. Do you have order processing which runs through a myriad business instructions? Do you have your users see a fascinating marvel called rotating hourglass and twiddle their thumbs after they submit an order? Wouldn't it make sense to break the transaction, put it on a order processing queue and let users know they would be informed when their order is processed? One can easily use some sort of queuing mechanism like MSMQ to decouple the component that submits the order from the service that actually processes the order. In the web scenario, one could use AJAX rather than having the user reload the entire web page again.
- Interface Design - It makes sense to design coarse grained interfaces a.k.a Chunky Interfaces to reduce the chatter among the software layers. It's best to have calls to retrieve and insert data in chunks rathen than invoking multiple method calls to achieve the same logical unit of work. For example, let's say you had an Order class, which had details about the Order, its LineItems and the details about the Customer. Would you have 3 separate calls to create Order, OrderLineItems and Customer or just have one call to create Order, which would execute a transaction to create the Customer if it doesn't exist and then save the Order and its LineItems. It would be prudent to have only one call rather than making 3 independent service calls to achieve this logical unit of work as it reduces the chatter between service layers and help boost performance.
- Data Partitioning - As the slowest moving piece of any application is I/O, it makes sense to give a lot of thought to the database design and how the data would be partitioned in it, if needed. There are times when certain datasets get used a lot, think of million of hits per day. In those scenarios, it makes sense to partition these datasets with the help of a partition key. The partition key decides how the data would be split physcially. For example, if you are building a social network and you get equal number of english, french and german speaking users then should you divide the users in different databases? It depends upon the context but one should think about the layout of the data persistence.
In MS SQL Server 2005, one could even partition a table without having the application ever to know about that the data is distributed in different filegroups.
Are there any special design considerations that you know of, which can help boost the performance?
